14 citations · 14 across the 6 of their papers we have counts for
7 papers
ACT-R: Adaptive Camera Trajectories for Single View 3D Reconstruction
Yizhi Wang, Mingrui Zhao, Hao Zhang
We introduce the simple idea of adaptive view planning to multi-view synthesis, aiming to improve both occlusion revelation and 3D consistency for single-view 3D reconstruction. In…
GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generation
Dingdong Yang, Yizhi Wang, Konrad Schindler +2
We propose GALA, a novel representation of 3D shapes that (i) excels at capturing and reproducing complex geometry and surface details, (ii) is computationally efficient, and (iii)…
SweepNet: Unsupervised Learning Shape Abstraction via Neural Sweepers
Mingrui Zhao, Yizhi Wang, Fenggen Yu +2
Shape abstraction is an important task for simplifying complex geometric structures while retaining essential features. Sweep surfaces, commonly found in human-made objects, aid in…
EASI-Tex: Edge-Aware Mesh Texturing from Single Image
Sai Raj Kishore Perla, Yizhi Wang, Ali Mahdavi-Amiri +1
We present a novel approach for single-image mesh texturing, which employs a diffusion model with judicious conditioning to seamlessly transfer an object's texture from a single RG…
AnaMoDiff: 2D Analogical Motion Diffusion via Disentangled Denoising
Maham Tanveer, Yizhi Wang, Ruiqi Wang +3
We present AnaMoDiff, a novel diffusion-based method for 2D motion analogies that is applied to raw, unannotated videos of articulated characters. Our goal is to accurately transfe…
Slice3D: Multi-Slice, Occlusion-Revealing, Single View 3D Reconstruction
Yizhi Wang, Wallace Lira, Wenqi Wang +2
We introduce multi-slice reasoning, a new notion for single-view 3D reconstruction which challenges the current and prevailing belief that multi-view synthesis is the most natural…
BRICS: Bi-level feature Representation of Image CollectionS
Dingdong Yang, Yizhi Wang, Ali Mahdavi-Amiri +1
We present BRICS, a bi-level feature representation for image collections, which consists of a key code space on top of a feature grid space. Specifically, our representation is le…